recommend_plan

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With annotations already declaring readOnlyHint=true and destructiveHint=false, the safety profile is covered. The description goes further by disclosing the exact return shape: a recommendation with plain-language reasons, a cheaper alternative when one fits, and a WhatsApp Meta Business Verification warning. This is exactly the kind of output-shape behavioral context annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: the first front-loads the action and its inputs, the second front-loads the return value and usage trigger. Every clause earns its place with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must explain returns — and it does, naming the recommendation, the cheaper alternative, and the WhatsApp verification warning. All 6 parameters are documented in the schema, and the usage trigger is explicit. Nothing needed to call this tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline would be 3. The description adds meaning by framing the parameters as discovery signals ('what you learn about the business in conversation'), telling the agent that these inputs are gathered progressively during dialogue rather than passed all at once. It doesn't add syntax details, which is appropriate given full schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (recommend) and resource (InstantReply plan) plus the inputs it consumes (channels, monthly volume, team size, API/webhook access). No sibling tool does anything similar, so it distinguishes itself implicitly and explicitly within a conversational sales context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The final sentence 'Use this before telling a user what to sign up for' gives a clear when-to-use trigger. The phrase 'from what you learn about the business in conversation' establishes the prerequisite context, leaving no ambiguity about timing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.